Bachelor of Technology (B.Tech.) in Computer Science and Artificial Intelligence (AI) is an undergraduate degree program that aims to provide students with a strong foundation in computer science and the rapidly expanding field of artificial intelligence. This curriculum combines academic knowledge with practical skills to equip students for careers in technology and AI-related industries.
Students will gain a broad understanding of computer science principles, programming languages, algorithms, data structures, and the quickly evolving field of artificial intelligence through the B.Tech. in Computer Science and AI curriculum. It allows students to thoroughly explore the subjects of robotics, machine learning, neural networks, and more by fusing traditional computer science topics with specialized AI courses.
Salient Features
Graduates of a B.Tech. in Computer Science and AI are well-prepared for a wide range of career opportunities, including:
- AI Engineer/Developer
- Machine Learning Engineer
- Data Scientist
- Computer Vision Engineer
- Natural Language Processing Engineer
- Robotics Engineer
- Software Engineer
- Research Scientist in AI
- AI Consultant
The B.Tech. in Computer Science and AI offers students a demanding and exciting curriculum while equipping them with the knowledge and skills they need to successfully navigate the rapidly evolving field of artificial intelligence. Since it blends core computer science concepts with complex AI ideas, graduates can contribute to cutting-edge innovations and discoveries in several industries.
Eligibility
Students must have passed Class 12 from NEB or equivalent with minimum C Grade/Second Division (Grade D in case of A-level) with Physics, Chemistry, and Mathematics
Curricular Structure
The curriculum of this program is designed to cover a broad spectrum of subjects, including:
Computer Science Fundamentals: The core of the computer science component consists of courses on programming languages, data structures, algorithms, databases, and computer networks.
Artificial Intelligence: Machine learning methods, deep learning, reinforcement learning, computer vision, natural language processing, and robotics are all topics covered in specialized AI courses. These programs prepare students to create AI-powered solutions by delving into the real-world applications of AI.
Mathematics and Statistics: Understanding the basic concepts of AI algorithms and models requires a solid background in mathematics and statistics. Statistics, deductive mathematics, and mathematics are frequently covered in these courses.
Software Engineering: Project management, software design patterns, and approaches for developing software are all topics that students study. These abilities are necessary for creating scalable and reliable AI applications.
Ethics and Social Implications: Courses on ethics, privacy, and the responsible use of AI are frequently included since AI technologies have significant societal repercussions. This encourages students to think about the ethical implications of their work.
Electives: According to their preferences, students can frequently select elective courses in natural language processing, computer vision, autonomous systems, and more advanced AI areas.